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1
Deriving the Operational Procedure for the
Universal Thermal Climate Index UTCI
Peter Bröde
1
, Dusan Fiala
2,3
, Krzysztof Błażejczyk
4
, Ingvar Holmér
5
, Gerd
Jendritzky
6
, Bernhard Kampmann
7
, Birger Tinz
8
, George Havenith
9
(1) Leibniz Research Centre for Working Environment and Human Factors
(IfADo), Ardeystr. 67, 44139 Dortmund, Germany
(2) Ergonsim – Comfort Energy Efficiency, Stuttgart, Germany
(3) Institute of Building Technologies, IBBTE, University of Stuttgart, Germany
(4) Institute of Geography and Spatial Organization, Polish Academy of Sciences,
Warsaw, Poland
(5) Department of Design Sciences, EAT, Lund University, Sweden
(6) Meteorological Institute, University of Freiburg, Germany
(7) Department of Safety Engineering, Bergische Universität Wuppertal, Germany
(8) German Meteorological Service, Department Climate Monitoring, Hamburg,
Germany
(9) Environmental Ergonomics Research Centre, Loughborough Design School,
Loughborough University, UK
Corresponding author:
Peter Bröde
Phone +49 231 1084 225
Fax +49 231 1084 400
e-mail: broede@ifado.de
http://www.ifado.de
Abstract
The Universal Thermal Climate Index (UTCI) aimed for a one-dimensional quantity adequately
reflecting the human physiological reaction to the multi-dimensionally defined actual outdoor
thermal environment. The human reaction was simulated by the UTIC-Fiala multi-node model of
human thermoregulation, which was integrated with an adaptive clothing model. Following the
concept of an equivalent temperature, UTCI for a given combination of wind speed, radiation,
humidity and air temperature was defined as the air temperature of the reference environment,
which according to the model produces an equivalent dynamic physiological response.
Operationalising this concept involved (i) the definition of a reference environment with 50%
relative humidity (but vapour pressure capped at 20 hPa), with calm air and radiant temperature
equalling air temperature and (ii) the development of a one-dimensional representation of the
*Manuscript
Click here to download Manuscript: IJBM-UTCI-Broede-revised.doc Click here to view linked References
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multivariate model output at different exposure times. The latter was achieved by principal
component analyses showing that the linear combination of 7 parameters of thermophysiological
strain (core, mean and facial skin temperatures, sweat production, skin wettedness, skin blood
flow, shivering) after 30 min and 120 min exposure time accounted for two thirds of the total
variation in the multi-dimensional dynamic physiological response. The operational procedure was
completed by a scale categorising UTCI equivalent temperature values in terms of thermal stress,
and by providing simplified routines for fast but sufficiently accurate calculation, which included
look-up tables of pre-calculated UTCI values for a grid of all relevant combinations of climate
parameters and polynomial regression equations predicting UTCI over the same grid.
The analyses of the sensitivity of UTCI to humidity, radiation and wind speed showed plausible
reactions as well in the heat as in the cold, and indicate that UTCI may in this regard be
universally useable in the major areas of research and application in human biometeorology.
Keywords: outdoor climate; index; thermal stress; thermophysiology; simulation
model; thermal comfort.
Introduction
Initiated by Commission 6 of the International Society of Biometeorology, and
developed with support from the European Union within the COST Action 730,
the Universal Thermal Climate Index UTCI aims at the assessment of the outdoor
thermal conditions in the major fields of human biometeorology. The UTCI
(Jendritzky et al. 2007) ultimately should provide a one-dimensional quantity
which adequately reflects the human physiological reaction to the multi-
dimensionally defined actual thermal condition. In an attempt to extend available
approaches using human heat budget models (Vanos et al. 2010; Kenny et al.
2009a; Höppe 1999), the human reaction was simulated by a multi-node model of
human thermoregulation, which was integrated with an adaptive clothing model.
As illustrated in Figure 1, the index value will be calculated from the multivariate
dynamic output of that model. The term “dynamic” refers to the time-dependency
of physiological responses in non-moderate conditions before reaching steady-
states. The concept was chosen to account for differences in the assessment of
indoor and outdoor climate conditions; the latter being characterised by diverse
dynamic effects in the human response to the wide range of outdoor
environments. Especially under exposure to cold, steady-state conditions might
not be achieved even after several hours (Höppe 2002).
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Following the pioneering work of Stolwijk (1971), a number of multi-segmental
thermoregulatory models emerged, which are more deeply discussed in this
special issue by Fiala et al. (2011). After accessible models of human
thermoregulation had been evaluated, the advanced multi-node „Fiala‟
thermoregulation model was selected (Fiala et al. 1999; Fiala et al. 2001), which
also provides for predicted votes of the dynamic thermal sensation based on core
and skin temperature signals (Fiala et al. 2003). Within the COST Action 730 the
physiological model was extensively validated (Psikuta et al. 2011), adapted and
extended for purposes of the project (Fiala et al. 2011). In the next step a state-of-
the-art adaptive clothing model was developed and integrated (Havenith et al.
2011). This model considers
1. the behavioural adaptation of clothing insulation observed for the general
urban population in relation to the actual environmental temperature,
2. the distribution of the clothing over different body parts providing local
insulation values for the different model segments, and
3. the reduction of thermal and evaporative clothing resistances caused by
wind and the movement of the wearer.
UTCI was then developed following the concept of an equivalent temperature.
This involved the definition of a reference environment, to which all other
climatic conditions are compared. Equal physiological conditions are based on the
equivalence of the dynamic physiological response predicted by the model for the
actual and the reference environment. As this dynamic response is
multidimensional (body core temperature, sweat rate, skin wettedness etc. at
different exposure times), a response index had to be calculated as single
dimensional representation of the model response, cf. Figure 1. The UTCI
equivalent temperature for a given combination of wind speed, radiation, humidity
and air temperature is then defined as the air temperature of the reference
environment, which produces the same response index value.
As calculating the UTCI equivalent temperatures by running the thermoregulation
model repeatedly would on the one hand require expert knowledge to operate with
the complex simulation software and, on the other hand, could be too time-
consuming for climate simulations and numerical weather forecasts, several
options for the operational procedure of UTCI to simplify this calculation were
considered. Some applications may also require the computed UTCI values to be
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categorised in terms of thermal stress (Staiger et al. 1997; Koppe and Jendritzky
2005).
The following sections delineate how the simulation model was used to derive
UTCI, how UTCI responds to wind, humidity and radiation under heat and cold
stress conditions, and how UTCI may be calculated and categorised by the
operational procedure in routine application.
Deriving UTCI from the model of thermoregulation
As described in introductory contributions to this special issue and also by
Gonzalez et al. (1974), expressing index values in terms of an equivalent
temperature constitutes a commonly applied concept which had already been
applied to develop the Effective Temperature (ET, Houghten and Yagloglou
1923), with later extensions such as ET* (Gagge et al. 1971) or the Standard
Effective Temperature (SET*, Gagge et al. 1986; Gonzalez et al. 1974) followed
by more recent modifications and developments (Parsons 2003; Höppe 1999;
Staiger et al. 1997). As operationalised here, the UTCI is defined as the air
temperature (Ta) of the reference condition causing the same model response as
the actual condition. The offset, i.e. the deviation of UTCI from air temperature
depends on the actual values of air and mean radiant temperature (Tr), wind speed
(va) and humidity, expressed as water vapour pressure (pa) or relative humidity
(rH), cf. Figure 1. This may be written in mathematical terms as
UTCI(Ta, Tr, va, pa) = Ta + Offset(Ta, Tr, va, pa) (1)
Applying this characterization requires the identification of both the reference
condition and the dynamic model response. The approach chosen by UTCI is
outlined below.
Reference condition
To convert climate impact to a single value and to facilitate the interpretation and
understanding of UTCI, reference conditions must be a) defined in terms
conforming to most people‟s experiences and b) relevant across the whole
spectrum of climate zones to which UTCI is going to be applied. Therefore the
non-meteorological variables metabolic rate MET and the thermal properties of
clothing (insulation, vapour resistance, air permeability) are of great importance.
